High Resting Heart Rate and High BMI Predicted Severe Coronary Atherosclerosis Burden in Patients With Stable Angina Pectoris by SYNTAX Score

Abstract

We investigated the independent and combined association of resting heart rate (RHR expressed as beats/min, bpm) and body mass index (BMI) with SYNTAX score (SS) in patients with stable angina. We divided 312 patients into 4 groups according to RHR quartiles: Q1 (<65 bpm), Q2 (65-69 bpm), Q3 (70-79 bpm), and Q4 (≥80 bpm). The SS (12.0 ± 9.0, 16.0 ± 15.5, 18.0 ± 16.5, and 20.0 ± 27.5; P < .001) was significantly higher for those in Q4 than for those in Q1, Q2, and Q3. Multivariate logistic regression analysis indicated that each 10-bpm increment in RHR was significantly associated with SS (odds ratio [OR] 1.62, 95% confidence interval [CI] 1.27-2.06). Patients with high RHR and high BMI had significantly greater odds ratio (OR) of high SS (4.03, 95% CI 2.00-8.14), compared to participants with low RHR and low BMI. Both RHR and BMI were independent predictors of coronary atherosclerosis as assessed by SS. RHR in combination with BMI and multivariate logistic regression analysis emphasized the importance of the correlation between RHR and SS in patients with stable angina pectoris.

Keywords

resting heart rate BMI atherosclerosis stable angina pectoris SYNTAX score

Introduction

Resting heart rate (RHR), an easily measured and inexpensive clinical parameter, is closely related to the prevalence of coronary heart disease (CHD) and adverse cardiovascular (CV) events in several large-scale studies^1
–3 in general populations. However, there is tenuous evidence why patients with high RHR are at risk of CHD or CV disease (CVD). The incremental occurrence of CHD and CV events may be associated with decreased CV efficiency or the extra hemodynamic shear and tensile stress from the superfluous number of pulse waves.⁴ Endothelial injury induced by the extra accumulation of vessel wall stress may increase circulating inflammatory mediators,⁵ finally provoking the development of atherosclerosis. Moreover, the elevated RHR induces shortening of diastolic period and increasing systolic duration and has a negative effect on myocardial energetics,⁶ resulting in the reduced cardiac perfusion and increased cardiac working.^3,7

Although the usefulness of RHR in predicting the CHD or CVD risk of morbidity and mortality in general populations has been reported, the impact of RHR for coronary atherosclerosis burden in patients with stable angina pectoris, especially the combined effect of RHR and other known risk factors on the severity and complexity of atherosclerosis, has not been clearly demonstrated. Obesity has been significantly correlated with an elevated mortality risk in general populations,^8,9 and several studies have revealed a significant association of obesity with increased CV events.^10
–12

At present, there are 4 scoring systems for assessing coronary angiographic lesion complexity, including Leaman score,¹³ American College of Cardiology/American Heart Association (ACC/AHA) score,^14
–16 Gensini score,¹⁷, and the Synergy between percutaneous coronary intervention with Taxus and cardiac surgery (SYNTAX) score (SS).¹⁸ The Leaman score and ACC/AHA score have been rarely used because of their limitations. For example, the Leaman score only includes lesions with ≥70% stenosis, and these 2 scoring systems have little value in predicting the major adverse cardiovascular events (MACEs) in patients with acute coronary syndrome (ACS).^18,19 Based on the first 2 scoring methods and other scoring systems, the SS is more comprehensive than the Gensini score, taking into account the characteristics of the lesion. The SS grades the complexity of CHD based on the coronary anatomy and lesion characteristics,^18,20 and higher scores imply a more complex CHD. Therefore, this score helps to select the appropriate revascularization strategy. Some studies^21

–24 revealed that the score was related to cardiac mortality and MACEs, and a high SS suggested a worse long-term outcome in patients who received percutaneous coronary intervention (PCI) revascularization. We aimed to assess the independent and combined association of RHR and BMI with coronary atherosclerosis burden assessed by SS in patients with stable angina pectoris.

Methods

Study Population

The population for this study comprised 312 patients with stable CHD at Xinhua Hospital, Shanghai, China, between January 2011 and June 2016. Patients with a diagnosis of stable angina pectoris with sinus rhythm for primary PCI (pPCI) or primary coronary angiography (CAG) were eligible if they were aged ≥18 years and with ≥50% stenosis in ≥1 coronary artery as assessed by CAG.

Exclusion Criteria

The exclusion criteria were as follows: (1) history of PCI or coronary artery bypass graft (CABG) surgery, (2) history of permanent pacemaker implantation, (3) abnormal liver or renal function, (4) heart failure (ejection fraction <50%), (5) acute or chronic infection, (6) thyroid disease, (7) nonsinus rhythm: atrial fibrillation and atrioventricular block, and (8) psychiatric disorders (Figure 1). This study was approved by the Ethics Committee of Experimental Research, Jiaotong University. Written informed consent was obtained from all patients.

We retrospectively analyzed the patients’ baseline characteristics: gender, age, BMI, hypertension, diabetes mellitus (DM), hyperlipidemia, smoking history, family history of CHD, current medication, systolic blood pressure (SBP), and diastolic blood pressure (DBP). Hypertension was diagnosed if SBP ≥140 mm Hg, DBP ≥90 mm Hg, or present usage of antihypertensive medication. DM was defined as fasting glucose ≥126 mg/dL (7.0 mmol/L) or present usage of antidiabetic medication. The diagnosis criteria for hyperlipidemia were one of the following: total cholesterol >200 mg/dL or usage of lipid-lowering drugs. Moreover, each participant was evaluated for hematological indices, serum glucose, liver and renal function, lipid profile, high-sensitivity C-reactive protein (hsCRP), and ejection fraction.

Resting Heart Rate

The measurement of RHR was based on routine 12-lead electrocardiography (ECG) after resting at least 10 minutes. Mean time between RHR measurement and CAG was 46 ± 13 hours.

Body Mass Index

The BMI was calculated as weight in kg divided by the square of height in m. Weight and height were measured by nurses when the patients were admitted to our hospital.

SYNTAX Score

Coronary angiography was performed via the radial artery according to standard clinical practice. The severity of coronary lesions was determined by SS. The arithmetic method of this score was reported previously,^18,25 and we performed the calculation using the software on the website (www.syntaxscore.com). Briefly, all lesions ≥50% stenosis in arteries larger than 1.5 mm were calculated and were given a weight factor associated with the location and severity of the lesions. The characteristics of lesions were added to the sum of the score, including total occlusion, trifurcation, bifurcation, aorto-ostial lesion, severe tortuosity, length >20 mm, heavy calcification, thrombus, and diffuse or small vessel disease. All the calculations were performed by 2 specialists blinded to the clinical and laboratory findings of the cases. For controversial lesions, a senior interventional cardiologist was consulted, and a final decision was made by consensus.

Statistical Analysis

All statistical analysis was performed with IBM SPSS Statistics 21.0 (SPSS, Inc, Chicago, Illinois). All participants were divided into 4 groups by RHR quartiles: <65, 65 to 69, 70 to 79, and ≥80 bpm. The normally distributed continuous data were expressed as mean ± standard deviation (SD), and the differences were compared by 1-way analysis of variance. Since the Kolmogorov-Smirnov test showed that alanine aminotransferase (ALT), total triglyceride (TG), and hsCRP had a nonnormal distribution, we used their log transformation form to analyze them. Nonnormal variates BMI, RHR, dosage of β-blocker, calcium channel blocker (CCB), and angiotensin-converting enzyme inhibitor/aldosterone receptor blocker (ACEI/ARB), SBP, DBP, SS, lesion arteries, aspartate aminotransferase (AST), fasting blood glucose, and creatinine were represented by median ± interquartile range (IQR) and compared by the Kruskal-Wallis H test. Categorical data were reported by percentage and compared to the chi-square test.

In order to determine the association of RHR and BMI with SS, we divided the participants into two groups: low SS (SS <23) and high SS (SS ≥23). The cutoff point of 23 was based on the original SYNTAX trial²⁶ and was used in previous studies.^27,28 A logistic analysis was used to estimate the relationship between high SS and each 10-bpm increment in RHR and BMI; then, a multivariate logistic analysis was used to assess whether RHR and BMI were the independent predictors of high SS.

We combined the primary dependable parameters RHR with BMI to form four groups: low RHR (<80 bpm) and low BMI (<25 kg/m²), low RHR and high BMI (≥25 kg/m²), high RHR (≥80 bpm) and low BMI, and high RHR and high BMI. An additional logistic analysis was performed to determine the relationship of combination of RHR and BMI with SS and adjusted for gender, age, hypertension, DM, smoking, family history, and hyperlipidemia. A 2-tailed P < .05 was considered significant, and the confidence interval (CI) was 95%.

Results

Baseline Clinical Demographics and Laboratory Parameters

Baseline characteristics are shown in Table 1. All comers were divided into 4 groups depending on the approximate quartiles of RHR, and the range of RHR in each group was 50 to 64, 65 to 69, 70 to 79, and 80 to 116 bpm. There were no significant differences in recent medications that may affect the heart rate like β-blockers, CCB, and ACEI/ARB, among the four groups according to RHR quartiles. Also, the dosage of β-blocker, CCB, and ACEI/ARB were not significantly different in these groups. All participants did not use other medicines that may affect heart rate, like ivabradine or digoxin. The SBP and DBP were significantly different among the 4 groups; however, patients with hypertension did not differ significantly. In these 4 groups, patients with higher RHR had a significantly higher SS (12.0 ± 9.0 vs 16.0 ± 15.5 vs 18.0 ± 16.5 vs 20.0 ± 27.5, respectively, P < 0.001; Figure 2). Compared to Q1, Q2, and Q3, Q4 had more lesion arteries (the number of arteries with ≥50% stenosis; 1.0 ± 1.0 vs 1.0 ± 1.0 vs 1.0 ± 1.0 vs 2.0 ± 2.0, respectively, P = .001). Laboratory parameters of the study population are summarized in Table 2.

Table 1.

Baseline Characteristics According to RHR Quartiles.

Variables	RHR Quartiles, bpm				P
Variables	Q1 (<65)	Q2 (65- 69)	Q3 (70- 79)	Q4 (≥80)	P
n	77	76	78	81	/
Male (%)	58 (75.3)	51 (67.1)	46 (59.0)	56 (69.1)	.183
Age, years	66.4 ± 8.9	63.5 ± 9.3	63.7 ± 9.7	65.0 ± 9.4	.195
BMI, kg/m²	24.2 ± 2.0	24.2 ± 3.2	23.6 ± 4.1	25.3 ± 2.4	.001
RHR, bpm	61.0 ± 3.0	67.0 ± 3.0	75.0 ± 6.0	86.0 ± 8.0	<.001
Systolic pressure, mm Hg	132.0 ± 19.0	136.0 ± 21.8	131.0 ± 18.0	140.0 ± 18.0	.006
Diastolic pressure, mm Hg	80.0 ± 13.5	80.0 ± 13.5	78.0 ± 10.0	80.0 ± 12.0	.022
Hypertension, n (%)	54 (70.1)	48 (63.2)	54 (69.2)	53 (65.4)	.774
Diabetes, n (%)	15 (19.5)	17 (22.4)	14 (17.9)	22 (27.2)	.512
Hyperlipidemia, n (%)	39 (50.6)	37 (48.7)	37 (47.4)	41 (50.6)	.972
Current smoking, n (%)	27 (35.1)	25 (32.9)	22 (28.2)	29 (35.8)	.742
Family history, n (%)	2 (2.6)	2 (2.6)	4 (5.1)	3 (3.7)	.853
Medications
Aspirin n (%)	13 (16.9)	20 (26.3)	19 (24.4)	19 (23.5)	.533
β-blocker n (%)	11 (14.3)	13 (17.1)	13 (16.7)	17 (21.0)	.733
Dosage of β-blocker, mg	23.8 ± 21.3	23.8 ± 16.3	23.8 ± 34.4	23.8 ± 18.8	.348
CCB, n (%)	31 (40.3)	23 (30.3)	29 (37.2)	30 (37.0)	.622
Dosage of CCB, mg	5.0 ± 25.0	5.0 ± 25.0	5.0 ± 25.0	5.0 ± 0.0	.238
ACEI/ARB, n (%)	29 (37.7)	23 (30.3)	25 (32.1)	27 (33.3)	.794
Dosage of ACEI/ARB, mg	80.0 ± 0.0	80.0 ± 0.0	80.0 ± 35.0	80.0 ± 30.0	.271
Statin, n (%)	9 (11.7)	14 (18.4)	13 (16.7)	17 (21.0)	.463
Hypoglycemic agent, n (%)	14 (18.2)	13 (17.1)	14 (17.9)	25 (30.9)	.102
LVEF, %	66.0 ± 5.4	66.5 ± 6.1	66.0 ± 6.8	65.0 ± 7.0	.935
SYNTAX score	12.0 ± 9.0	16.0 ± 15.5	18.0 ± 16.5	20.0 ± 27.5	<.001
Lesion arteries	1.0 ± 1.0	1.0 ± 1.0	1.0 ± 1.0	2.0 ± 2.0	.001

Abbreviations: BMI, body mass index; RHR, resting heart rate; CCB, calcium channel blocker; ACEI/ARB, angiotensin-converting enzyme inhibitor/aldosterone receptor blocker; LVEF, left ventricular ejection fraction; bpm, beats/min.

Table 2.

Participants’ Laboratory Parameters.

Variables	RHR Quartiles, bpm				P
Variables	Q1 (<65)	Q2 (65-69)	Q3 (70-79)	Q4 (≥80)	P
Hemoglobin, g/L	137.8 ± 12.8	137.3 ± 13.4	135.3 ± 13.2	138.6 ± 14.8	.475
Platelets, ×10⁹/L	192 ± 51	206 ± 57	207 ± 50	194 ± 51	.126
Leukocyte count, ×10⁹/L	6.4 ± 1.7	6.2 ± 1.7	6.2 ± 1.6	6.3 ± 1.5	.852
ALT, U/L	18 ± 2	19 ± 2	19 ± 2	20 ± 2	.787
AST, U/L	19 ± 9	20 ± 6	19 ± 8	20 ± 10	.753
Fasting blood glucose, mmol/L	5.3 ± 1.1	5.2 ± 1.0	5.4 ± 1.1	5.7 ± 1.4	.173
Total cholesterol, mmol/L	4.5 ± 1.2	4.2 ± 1.2	4.4 ± 1.0	4.4 ± 1.1	.446
Total triglyceride, mmol/L	1.6 ± 1.7	1.5 ± 1.7	1.4 ± 1.7	1.6 ± 1.7	.575
HDL, mmol/L	1.1 ± 0.2	1.2 ± 0.3	1.2 ± 0.3	1.2 ± 0.2	.321
LDL, mmol/L	2.5 ± 0.8	2.3 ± 0.7	2.4 ± 0.7	2.4 ± 0.7	.414
hsCRP^a, mg/L	1.0 ± 3.6	0.8 ± 3.3	0.8 ± 4.4	0.9 ± 3.3	.648
Creatinine, µmol/L	72 ± 21	70 ± 19	69 ± 16	69 ± 22	.683
Uric acid, µmol/L	363 ± 83	355 ± 102	327 ± 85	353 ± 70	.054

Abbreviations: ALT, alanine aminotransferase; AST, aspartate aminotransferase; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; hsCRP, high-sensitivity C-reactive protein; RHR, resting heart rate.

^aCalculated for the 175 patients with available hsCRP data.

The Respective Effect and Combined Impact of RHR and BMI on the SS

According to a univariate logistic analysis, each 10-bpm increment in RHR was correlated with greater odds of an SS above 23 (OR 1.69, 95% CI 1.34-2.13, P <.001). Likewise, the odds of having a high SS for each 1 kg/m² increment in BMI was 1.17 (95% CI 1.06-1.29, P = .002). After adjusting for gender, age, hypertension, diabetes, smoking, family history, hyperlipidemia, BMI, or RHR, each 10-bpm increment in RHR (OR 1.62, 95% CI 1.27-2.06, P < .001) and BMI (OR 1.12, 95% CI 1.01-1.25, P = .034) also reached statistical significance (Table 3); thus, RHR and BMI were independent predictors of the SS.

Table 3.

ORs of High SS in Univariate and Multivariate Logistic Regression Analysis.^a

Total	RHR (10 Increment)		BMI
Total	OR	P	OR	P
No adjusted OR (95% CI)	1.69 (1.34-2.13)	<.001	1.17 (1.06 to 1.29)	.002
Multivariable-adjusted OR (95% CI)	1.62 (1.27-2.06)	<.001	1.12 (1.01 to 1.25)	.034

Abbreviations: RHR, resting heart rate; BMI, body mass index; OR, odds ratio; CI, confidence interval; SS, Syntax score.

^aAdjusted for gender, age, hypertension, diabetes, smoking, family history, hyperlipidemia, BMI, or RHR.

In order to assess the combination impact of RHR and BMI on SS, we divided the participants into 4 groups according to RHR and BMI: low RHR (<80 bpm) and low BMI (<25 kg/m²), low RHR and high BMI (≥25 kg/m²), high RHR (≥80 bpm) and low BMI, and high RHR and high BMI. According to a multivariate logistic regression analysis adjusted for gender, age, hypertension, diabetes, smoking, family history, and hyperlipidemia, patients with high RHR and high BMI had significantly greater odds of high SS (OR 4.03, 95% CI 2.00-8.14, P < .001), compared to participants in the low RHR and low BMI group. Likewise, patients in the high RHR and low BMI group (OR 2.72, 95% CI 1.21-6.15, P = .016) and the low RHR and high BMI group (OR 1.96, 95% CI 1.03 to 3.74, P = .040) had significantly higher odds of having a high SS, compared to the low RHR and low BMI group after the same adjustment (Table 4).

Table 4.

ORs of High SS According to the Combination of RHR and BMI.^a

Total	RHR <80		RHR ≥80
Total	BMI <25 (n = 160)	BMI ≥25 (n = 71)	BMI <25 (n = 33)	BMI ≥25 (n = 48)
Events no.	30/160 (18.8%)	23/71 (32.4%)	13/33 (39.4%)	23/48 (47.9%)
No adjusted OR (95% CI)	1	2.08 (1.10-3.92)	2.82 (1.26-6.29)	3.99 (2.00-7.96)
Multivariable-adjusted OR (95% CI)	1	1.96 (1.03-3.74)	2.72 (1.21-6.15)	4.03 (2.00-8.14)

Abbreviations: RHR, resting heart rate; BMI, body mass index; OR, odds ratio; CI, confidence interval; SS, Syntax score.

^aAdjusted for gender, age, hypertension, diabetes, smoking, family history, and hyperlipidemia.

Discussion

In this study, we used univariate and multivariate logistic regression analysis to evaluate the association between RHR, BMI, and coronary atherosclerosis burden (assessed by the SS) in patients with stable angina pectoris. We found that both the RHR and BMI were independent predictors of coronary atherosclerosis by SS, after adjusting for gender, age, hypertension, diabetes, smoking, family history, and hyperlipidemia.

The SS is a practical tool to assess the magnitude and complexity of atherosclerosis.^18,20 Based on the original SYNTAX trial²⁶ which divided patients by tertile cutoffs (<23, 23 to 32 and >32), we used the cut point of 23 to perform further analysis in our study. We excluded patients with a history of PCI or CABG, because these processes may affect the determination of the SS. Analysis of the correlation between RHR and SS indicated that each 10-bpm increment in RHR was related to a 62% increase in the risk of high SS (≥23), after adjusting for gender, age, hypertension, DM, smoking, family history, hyperlipidemia, and BMI. This is consistent with another study²⁷ which reported that the SS was significantly higher for participants with RHR ≥77 bpm than for those RHR ≤65 bpm and RHR between 66 and 76 bpm (7.6 ± 4.6, 12.4 ± 5.6, 20.3 ± 8.1, respectively, P < .001). Other studies have reported that high RHR was related to the prevalence of myocardial infarction,¹ CHD,²⁹ and ischemic stroke¹ and was correlated with increased risk for adverse CV events, CV, and all-cause death in patients with stable chronic CVD.³⁰

Further analyses were conducted in the study; we divided the patients into 4 groups to investigate the conjunct association of RHR and BMI on high SS. The cut point 80 bpm of RHR used in the study has been usually used in previous research,^31
–33 and BMI ≥25 kg/m² is the World Health Organization Asian BMI standard for obesity.³⁴ Participants with higher BMI (≥25 kg/m²) showed higher odds of SS than participants with lower BMI (<25 kg/m²), compared to the respective RHR group. However, participants with a BMI of <25 kg/m² and RHR ≥80 bpm showed higher odds of coronary atherosclerosis burden than participants with a BMI of ≥25 kg/m² and RHR of <80 bpm. Moreover, an additional multiple regression analyses revealed that both RHR and BMI were significant predictors of high SS. This study demonstrated that both high RHR and high BMI were good indicators for the increased risk of coronary atherosclerosis burden in patients with stable angina pectoris.

To date, the role of RHR as a predictor or risk factor for the morbidity and mortality of CHD or CVD has been clearly demonstrated.^1
–3,29,30 Recent studies indicated that RHR may play an important role in the pathophysiology of atherosclerosis. Autonomic dysfunction and elevated mechanical load (ie, altered tensile or shear stress) on arterial wall were supposed to grant a predisposition to atherosclerosis,⁴ and these proatherosclerotic mechanisms were a possible result of high RHR. The intensive magnitude of tensile stress imposed on the endothelium upregulates proatherosclerotic gene expression,³⁵ and induces vascular smooth muscle cell proliferation and collagen deposition,³⁶ resulting in vascular stiffening. Endothelial injury induced by the elevated RHR enhances circulating inflammation factors,⁴ which play a crucial role in the accelerated process of atherosclerosis.⁵

The BMI is a conventional predictor of CHD or CVD.^9,10,37 In the study, we found that participants with higher BMI were more likely to have a higher atherosclerosis burden. The analysis of combined effect of RHR and BMI on SS showed that participants with high RHR and high BMI were associated with >4 times increase in the risk of high SS (≥23), compared to those with low RHR and low BMI. In accordance with our study, Juonala et al¹² followed up 6328 patients for 23 years and found that overweight or obese children who were obese as adults had elevated risk of hypertension and carotid artery atherosclerosis. A study of 5124 Korean adults reported that the participants with higher RHR (>80 bpm) and higher BMI (≥25 kg/m²) had 1.43 higher odds of hypertension and 1.91 higher odds of type 2 diabetes mellitus compared to those with lower RHR (≤80 bpm) and lower BMI (<25 kg/m²).³⁸ High BMI usually means a lower level of physical activity or an unhealthy diet, and the former is related to high risk of metabolic disease³⁹ and CVD.⁴⁰

As mentioned earlier, RHR and BMI were predictors for the prevalence of CHD or CVD and good predictors for major adverse CV events.^{1
–3,8

–12} We found that patients with high RHR and high BMI were associated with 4-fold increase in the risk of high SS, compared to those with low RHR and low BMI. In the future, to exploring the relationship between RHR, BMI, and other noninvasive or invasive imaging modalities, such as fractional flow reserve, will be interesting. It may be promising to study whether interventions aiming to decrease RHR and BMI could prevent the morbidity and mortality of stable CHD.

Our study suggested that in patients with stable CHD, RHR, and BMI were each independent predictors of atherosclerosis burden as assessed by the SS. This study provided evidence suggesting that the use of RHR is a practical method to recognize a high-risk population (BMI ≥25 kg/m²) and what would be considered low-risk population (BMI <25 kg/m²).

Our study has some limitations. First, we excluded participants with systemic and psychiatric disorders that may influence RHR, and the results in some participants may be affected by some unpredictable factors. Second, the data of RHR were obtained from the first ECG examination after admission. However, heart rate fluctuates during the day. Third, although RHR as a predictor of atherosclerotic burden has been clearly demonstrated, interventions to decrease RHR aiming to prevent the mortality and morbidity of stable CHD need further investigation.

Footnotes

Authors’ Note

All authors made substantial contributions to (1) conception and design, or acquisition of data, or analysis and interpretation of data, and (2) drafting the article or revising it critically for important intellectual content. All authors approved the final version to be published.

Declaration of Conflicting Interests

The author(s) declared no potential conflict of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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